Fundamental to curing a variety of disorders that affect learning and memory is an understanding of how learning and memory occur. That is, now that we are beginning to understand the cellular and subcellular events that lead to synaptic modification, it is time to ask how such microscopic changes are integrated into, and used by, the functioning nervous system. As our current knowledge stands, it is far from obvious how stored memories of polysensory events that occur In a temporally distributed manner (e.g., I spent yesterday afternoon at the grocery store) can be recalled and used by the brain as a more or less discretely coded event. It is our long-term objective to explain such issues of learning and memory in terms of information processing. To accomplish this objective the proposed research aims to create a quantitative theory that defines information processing in different brain regions as a function of synaptic modifiability, neuronal physiologies, and neuroanatomies. The research I will perform in the next five years is both experimental and theoretical although this application concentrates on the theoretical investigations. The experimental research consists of basic physiological and anatomical studies of the hippocampus, particularly studies of synaptic modification. The theoretical studies are at three levels: 1) single cell biophysics that integrate the quantitative knowledge obtained from the anatomical and physiological studies; 2) network models that integrate our knowledge of cellular and subcellular processes into quantitative models of the hippocampus in terms of information processing by this brain region; and 3) development of a basic theory of information processing for isolated brain regions. The research development includes studying hippocampal-like networks capable of synaptic modification using abstract measures of information processing. The professional growth includes developing my abstract theories in a direction that can be experimentally tested. Thus, I will collaborate with scientists who study behaving animals and correlated single-unit firing. The proposal describes a network theory. This developing theory seeks to define and understand information processing in the hippocampus. The research discussed in this application implicitly assumes the architectures and cellular physiologies of the hippocampus as they are currently understood or as they might actually be (given the limits of the biological research performed to date). The problem of accurate prediction, as is required of small animals in a spatial task, focuses our attention on a specific problem for which the hippocampus is relevant. By arriving at an abstract definition of any prediction problem and by considering certain basic facts of the nervous system in the context of the theory of computational complexity, we develop the issue of preprocessing signals in a hippocampal-like neural network. This preprocessing is a recoding that temporally compresses and statistically simplifies temporally distributed, polysensory signals. This preprocessing improves the quality of a prediction given the limitation of neurons and synapses as computational elements.